Registro público
Informe de salud del softwareesquema 0.27.0 · métricas 1.13.0 · 2026-07-26 21:40 UTC

microsoft / graphrag

A modular graph-based Retrieval-Augmented Generation (RAG) system

Python · Jupyter NotebookMIT★ 34.856 estrellas⑂ 3673 forksdesde mar 2024Ver en GitHub ↗

microsoft/graphrag tiene un índice de salud de 83 sobre 100, lo que lo sitúa en la banda Bueno. Su puntuación más alta es Community & Adoption (92/100) y la más baja, AI Readiness (54/100). Se actualizó por última vez hoy. 2 personas concentran la mayor parte del trabajo reciente.

83
global / 100
Bueno

Índice de salud del software

Las métricas se agrupan en categorías ponderadas sobre una escala de 1 a 100. El resultado global parte de su media; cuando la evidencia pública activa la Política de Jurisdicciones de Alto Riesgo, la calificación se ajusta y recibe el límite 49 (En riesgo). Preparación para IA queda fuera.

83
Excelente85-100Ejemplar; cumple prácticamente todos los criterios evaluados
Bueno70-84Saludable; carencias menores
Moderado50-69Aceptable con carencias notables; se recomienda revisión
En riesgo30-49Debilidades significativas; su adopción exige cautela
Crítico1-29Problemas graves (proyecto abandonado, un solo mantenedor, sin higiene)
VitalidadComunidad yAdopciónSostenibilidady GobernanzaCalidad deIngenieríaSeguridadPreparaciónpara IA

Perfil de puntuación

Cada eje es una categoría. La forma importa más que la media: un proyecto sano llena toda la figura, mientras que un perfil de picos y cráteres indica que la fortaleza en una dimensión enmascara el riesgo en otra.

Titularidad

MicrosoftOrganización
125.928 seguidores8222 repositorios públicosdesde dic 2013

Este repositorio está respaldado por una organización: una custodia compartida y responsable que puede sobrevivir a cualquier mantenedor individual.

Ecosistemas de paquetes

RegistroPaqueteVersiónDescargas / mesVersionesÚltima publicación
PyPIgraphrag3.1.174.78847hace 8 días
PyPIgraphrag-llm3.1.1-12hace 8 días
PyPIgraphrag-cache3.1.1-12hace 8 días
PyPIgraphrag-input3.1.1-12hace 8 días
PyPIgraphrag-common3.1.131.98112hace 8 días
PyPIgraphrag-storage3.1.1-12hace 8 días
PyPIgraphrag-vectors3.1.1-12hace 8 días
PyPIgraphrag-chunking3.1.1-12hace 8 días

Métricas por categoría

Vitalidad

¿Está vivo el proyecto: se escribe código y se publican versiones?

87Excelente · 22% del índice global
Cómo se puntúa
36/36Recencia de push — último push hace 0 días
15.9/36Cadencia de commits — 23/52 semanas con commits
17.4/18Volumen de commits — 85 commits en el último año
10/10OpenSSF Scorecard: Maintained — 14 commit(s) and 8 issue activity found in the last 90 days -- score normalized to 10
Datos de entrada utilizados
commits_last_year85
human_commit_share1
days_since_last_push0
active_weeks_last_year23
Cómo se puntúa
27/27Publica versiones — 41 versiones publicadas
36/36Recencia de las versiones — última versión hace 8 días
27/27Cadencia de publicación — una versión cada ~18,9 días
0/10OpenSSF Scorecard: Signed-Releases — sin datos
Datos de entrada utilizados
releases_count41
latest_release_tagv3.1.1
releases_from_tagsno
days_since_latest_release8
mean_days_between_releases18,9
Excluidos de la puntuación (sin datos o no aplicable): OpenSSF Scorecard: Signed-Releases. Los pesos restantes se han renormalizado.

Comunidad y Adopción

¿Tiene el proyecto usuarios, descargas, atención y unas condiciones acogedoras para quienes contribuyen?

92Excelente · 18% del índice global
Cómo se puntúa
60/60Estrellas — 34.856 estrellas
25/25Forks — 3673 forks
12.7/15Observadores — 196 observadores
Datos de entrada utilizados
forks3673
stars34.856
watchers196
growth_stateunverified
growth_factor_pct100
growth_unverified_reasonno_history
Cómo se puntúa
22.5/22.5README
22.5/22.5Licencia — licencia reconocida (MIT)
18/18Guía CONTRIBUTING
13.5/13.5Código de conducta
0/7.2Plantilla de issues
6.3/6.3Plantilla de PR
Datos de entrada utilizados
has_readme
has_license
has_contributing
has_issue_templateno
has_code_of_conduct
has_pull_request_template
Cómo se puntúa
67/80Descargas mensuales — 106.769 descargas/mes en pypi
0/20Dependientes en el registro — no lo informa este ecosistema
Datos de entrada utilizados
packagesgraphrag, graphrag-llm, graphrag-cache, graphrag-input, graphrag-common, graphrag-storage, graphrag-vectors, graphrag-chunking
dependents
ecosystemspypi
total_downloads
monthly_downloads106.769
Excluidos de la puntuación (sin datos o no aplicable): Dependientes en el registro. Los pesos restantes se han renormalizado.

Sostenibilidad y Gobernanza

¿Sobrevivirá el proyecto a sus personas: factor bus, capacidad de respuesta, quién lo respalda y mantenimiento del paquete?

80Bueno · 24% del índice global
Cómo se puntúa
25.2/54Factor bus — la mitad de los commits recae en 2 contribuyente(s)
15.1/22.5Distribución de commits — el principal contribuyente firma el 33% de los commits
13.5/13.5Amplitud de contribuyentes — 49 contribuyentes
10/10OpenSSF Scorecard: Contributors — project has 9 contributing companies or organizations
Datos de entrada utilizados
bus_factor2
contributors_sampled49
top_contributor_share0,329
Cómo se puntúa
46.5/46.8Resolución de issues — 100% de issues cerradas
23.6/38.3Aceptación de PR — 746/1209 PR decididos fusionados
15/15OpenSSF Scorecard: Code-Review — all changesets reviewed
Datos de entrada utilizados
merged_prs746
open_issues4
closed_issues828
issue_closed_ratio0,995
closed_unmerged_prs463
Cómo se puntúa
30/30Respaldo de la propiedad — propiedad de una organización
0/20Dominio verificado
25/25Alcance del propietario — 125.928 seguidores de microsoft
25/25Trayectoria — 8222 repos públicos, cuenta de ~12 años
Datos de entrada utilizados
followers125.928
owner_typeOrganization
is_verified
owner_loginmicrosoft
public_repos8222
account_age_days4611
Cómo se puntúa
25/25Publicado y resoluble — 8 paquete(s) en pypi
35/35Recencia de publicación — última publicación hace 8 días
20/20Historial de versiones — 47 versiones en el registro
20/20No obsoleto — activo, ni obsoleto ni retirado
Datos de entrada utilizados
packagesgraphrag, graphrag-llm, graphrag-cache, graphrag-input, graphrag-common, graphrag-storage, graphrag-vectors, graphrag-chunking
ecosystemspypi
any_deprecatedno
min_days_since_publish8

Calidad de Ingeniería

¿Existen unas prácticas mínimas de ingeniería y documentación?

81Bueno · 20% del índice global
Cómo se puntúa
24/24Flujos de trabajo de CI — 10 flujo(s) de trabajo
24/24Pruebas presentes
0/16Configuración de linter
0/9.6Hooks de pre-commit
0/6.4.editorconfig
20/20OpenSSF Scorecard: CI-Tests — 30 out of 30 merged PRs checked by a CI test -- score normalized to 10
Datos de entrada utilizados
has_ci
has_tests
has_editorconfigno
has_linter_configno
has_precommit_configno

Documentación

100Excelente
Cómo se puntúa
30/30README
25/25Directorio de documentación
15/15Sitio de documentación / página del proyecto — https://microsoft.github.io/graphrag/
10/10Descripción del repositorio
10/10Topics — 7 topics
10/10Wiki
Datos de entrada utilizados
topicsgraphrag, rag, llm, llms, gpt, gpt-4, gpt4
has_wiki
homepagehttps://microsoft.github.io/graphrag/
has_readme
has_docs_dir
has_description

Seguridad

¿Son sólidas las prácticas visibles de seguridad y de cadena de suministro, sin exposición jurisdiccional de alto riesgo sin resolver?

73Bueno · 16% del índice global
Cómo se puntúa
7.5/7.5Binary-Artifacts — no binaries found in the repo
3.8/7.5Branch-Protection — branch protection is not maximal on development and all release branches
2.5/2.5CI-Tests — 30 out of 30 merged PRs checked by a CI test -- score normalized to 10
0/2.5CII-Best-Practices — no effort to earn an OpenSSF best practices badge detected
7.5/7.5Code-Review — all changesets reviewed
2.5/2.5Contributors — project has 9 contributing companies or organizations
10/10Dangerous-Workflow — no dangerous workflow patterns detected
7.5/7.5Dependency-Update-Tool — update tool detected
0/5Fuzzing — project is not fuzzed
2.5/2.5Licencia — license file detected
7.5/7.5Maintained — 14 commit(s) and 8 issue activity found in the last 90 days -- score normalized to 10
0/5Packaging — sin datos
0/5Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 0
5/5SAST — SAST tool is run on all commits
5/5Security-Policy — security policy file detected
0/7.5Signed-Releases — sin datos
0/7.5Token-Permissions — detected GitHub workflow tokens with excessive permissions
0/7.5Vulnerabilities — 85 existing vulnerabilities detected
Datos de entrada utilizados
sourceopenssf_scorecard
checks_evaluated16
scorecard_versionv5.5.0
checks_inconclusive2
scorecard_aggregate6,6
Excluidos de la puntuación (sin datos o no aplicable): packaging, signed_releases. Los pesos restantes se han renormalizado.
Cómo se puntúa
35/35Dependencias directas libres de avisos conocidos — ninguna dependencia directa tiene un aviso conocido
25/25Dependencias indirectas libres de avisos conocidos — ninguna dependencia indirecta tiene un aviso conocido
0/40Sin avisos pendientes — ningún aviso tiene fecha de publicación
Datos de entrada utilizados
sourceosv
advisories0
affected_packages0
assessed_packages113
unassessed_packages0
affected_by_severitynone
direct_affected_packages0
Excluidos de la puntuación (sin datos o no aplicable): Sin avisos pendientes. Los pesos restantes se han renormalizado. Se cotejó el cierre de dependencias en tiempo de ejecución de pypi:graphrag@3.1.1 —lo que arrastra la instalación del paquete publicado—: 113 paquetes. No se analiza la alcanzabilidad.

Preparación para IA

¿Hasta qué punto está el repositorio preparado para desarrollarse y mantenerse con agentes de codificación de IA? Es una insignia independiente y experimental — peso 0,0, de modo que se presenta por separado y no afecta a la puntuación de salud global.

54Moderado · 0% del índice global
Cómo se puntúa
0/45Instrucciones para agentes — sin CLAUDE.md / AGENTS.md / reglas de editor
0/15Documentación legible por máquinas (llms.txt)
40/40Historial de commits legible — 99 de 100 commits humanos declaran su intención (asunto estructurado o cuerpo explicativo)
Datos de entrada utilizados
has_llms_txtno
legible_history_share0,99
agent_instruction_files
agent_instruction_max_bytes
Cómo se puntúa
0/18Arranque con un solo comando
22/22Pruebas automatizadas
0/11Configuración de lint / formato
11/11Verificación estática de tipos — packages/graphrag-cache/graphrag_cache/py.typed, packages/graphrag-common/graphrag_common/py.typed, packages/graphrag-llm/graphrag_llm/py.typed, packages/graphrag-storage/graphrag_storage/py.typed, packages/graphrag/graphrag/py.typed
10/10Entorno reproducible — Dockerfile, lockfile
10/10Práctica demostrada con agentes — 7 de los últimos 100 commits con autoría o crédito de agente
5/8Mantenimiento automatizado — automatización de dependencias configurada, no observada en los commits muestreados
0/10OpenSSF Scorecard: Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 0
Datos de entrada utilizados
has_nixno
has_tests
lockfilesuv.lock
has_dockerfile
typed_languageno
bootstrap_files
has_devcontainerno
has_linter_configno
typecheck_configspackages/graphrag-cache/graphrag_cache/py.typed, packages/graphrag-common/graphrag_common/py.typed, packages/graphrag-llm/graphrag_llm/py.typed, packages/graphrag-storage/graphrag_storage/py.typed, packages/graphrag/graphrag/py.typed
agent_commit_share0,07
toolchain_manifests
dependency_bot_commit_share0
Cómo se puntúa
27/45Código verificable por tipos — Python con configuración de verificación de tipos (packages/graphrag-cache/graphrag_cache/py.typed, packages/graphrag-common/graphrag_common/py.typed, packages/graphrag-llm/graphrag_llm/py.typed, packages/graphrag-storage/graphrag_storage/py.typed, packages/graphrag/graphrag/py.typed)
55/55Tamaños de archivo manejables — 0/573 archivos fuente de más de 60 KB
Datos de entrada utilizados
primary_languagePython
largest_source_bytes22.070
source_files_sampled573
oversized_source_files0
Cómo se puntúa
0/40Esquema de API (OpenAPI/GraphQL/proto)
0/20Servidor MCP
40/40Ejemplos ejecutables — notebooks
Datos de entrada utilizados
example_dirsnotebooks
has_mcp_signalno
api_schema_files

Datos clave

34.856estrellas de GitHub
49contribuidores
85commits en los últimos 12 meses
0días desde el último push
41versiones publicadas
2factor bus
4issues abiertas
PyPIecosistemas de paquetes

Advertencias de recopilación de datos

  • Star history unavailable: GitHub GraphQL error: Resource not accessible by personal access token
  • Could not fetch pypi package 'graphrag-monorepo' from its registry
  • Could not fetch pypi package 'unified-copilot' from its registry

Más detalle

Historial de estrellas y forks 0 ★ / 3673 ⇿
0Estrellas
3673Forks
15Versiones

Cuándo se añadió cada estrella y fork, recopilado de GitHub y agrupado por día. El crecimiento acumulado se sitúa justo encima de las adiciones diarias que lo componen, de modo que ambos se leen en conjunto: la acumulación orgánica sostenida no se parece en nada a un pico abrupto y efímero. Cuando esa diferencia es medible, se informa como autenticidad del crecimiento.

Solo se muestra el historial más reciente: este repositorio supera la ventana de recopilación, por lo que no se captura el historial más antiguo.

2500275030003250350037503673122025-082026-012026-07
Mayor 1Menor 3Parche 10
OpenSSF Scorecard 6.6 / 10
6.6agregado

Evaluación de seguridad independiente y agnóstica en cuanto a herramientas, procedente del proyecto de código abierto OpenSSF Scorecard. Cada comprobación premia una práctica de seguridad, no la herramienta de un proveedor concreto. Las comprobaciones que Scorecard no pudo determinar se marcan como n/d y se excluyen de la puntuación de seguridad (nunca se cuentan como cero).Scorecard v5.5.0 · 2026-07-26 21:40 UTC

10Binary-Artifactsno binaries found in the repo
5Branch-Protectionbranch protection is not maximal on development and all release branches
10CI-Tests30 out of 30 merged PRs checked by a CI test -- score normalized to 10
0CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
10Code-Reviewall changesets reviewed
10Contributorsproject has 9 contributing companies or organizations
10Dangerous-Workflowno dangerous workflow patterns detected
10Dependency-Update-Toolupdate tool detected
0Fuzzingproject is not fuzzed
10Licenselicense file detected
10Maintained14 commit(s) and 8 issue activity found in the last 90 days -- score normalized to 10
n/dPackagingpackaging workflow not detected
0Pinned-Dependenciesdependency not pinned by hash detected -- score normalized to 0
10SASTSAST tool is run on all commits
10Security-Policysecurity policy file detected
n/dSigned-Releasesno releases found
0Token-Permissionsdetected GitHub workflow tokens with excessive permissions
0Vulnerabilities85 existing vulnerabilities detected
Dependencias directas 72
RegistroPaqueteRestricción de versiónManifiesto
PyPIstreamlit==1.43.0unified-search-app/pyproject.toml
PyPIazure-search-documents~=11.4unified-search-app/pyproject.toml
PyPIazure-storage-blob~=12.20unified-search-app/pyproject.toml
PyPIazure-identity~=1.16unified-search-app/pyproject.toml
PyPIgraphrag==2.5.0unified-search-app/pyproject.toml
PyPIaltair~=5.3unified-search-app/pyproject.toml
PyPIstreamlit-agraph~=0.0.45unified-search-app/pyproject.toml
PyPIst-tabs~=0.1unified-search-app/pyproject.toml
PyPIspacy~=3.8unified-search-app/pyproject.toml
PyPIgraphrag-common==3.1.1packages/graphrag-cache/pyproject.toml
PyPIgraphrag-storage==3.1.1packages/graphrag-cache/pyproject.toml
PyPIgraphrag-common==3.1.1packages/graphrag-chunking/pyproject.toml
PyPIpydantic~=2.10packages/graphrag-chunking/pyproject.toml
PyPIpython-dotenv~=1.0packages/graphrag-common/pyproject.toml
PyPIpyyaml~=6.0packages/graphrag-common/pyproject.toml
PyPItoml~=0.10packages/graphrag-common/pyproject.toml
PyPIgraphrag-common==3.1.1packages/graphrag-input/pyproject.toml
PyPIgraphrag-storage==3.1.1packages/graphrag-input/pyproject.toml
PyPIpydantic~=2.10packages/graphrag-input/pyproject.toml
PyPImarkitdown~=0.1.0packages/graphrag-input/pyproject.toml
PyPIpyarrow>=14.0.0packages/graphrag-input/pyproject.toml
PyPIazure-identity~=1.25packages/graphrag-llm/pyproject.toml
PyPIfastapi>=0.136.3,<1.0packages/graphrag-llm/pyproject.toml
PyPIgraphrag-cache==3.1.1packages/graphrag-llm/pyproject.toml
PyPIgraphrag-common==3.1.1packages/graphrag-llm/pyproject.toml
PyPIjinja2~=3.1packages/graphrag-llm/pyproject.toml
PyPIlitellm==1.92.0packages/graphrag-llm/pyproject.toml
PyPInest-asyncio2~=1.7packages/graphrag-llm/pyproject.toml
PyPIorjson>=3.11.6,<4.0packages/graphrag-llm/pyproject.toml
PyPIpydantic~=2.10packages/graphrag-llm/pyproject.toml
PyPItyping-extensions~=4.12packages/graphrag-llm/pyproject.toml
PyPIaiofiles~=25.1packages/graphrag-storage/pyproject.toml
PyPIazure-cosmos~=4.9packages/graphrag-storage/pyproject.toml
PyPIazure-identity~=1.25packages/graphrag-storage/pyproject.toml
PyPIazure-storage-blob~=12.24packages/graphrag-storage/pyproject.toml
PyPIgraphrag-common==3.1.1packages/graphrag-storage/pyproject.toml
PyPIpandas~=3.0packages/graphrag-storage/pyproject.toml
PyPIpydantic~=2.10packages/graphrag-storage/pyproject.toml
PyPIazure-core~=1.32packages/graphrag-vectors/pyproject.toml
PyPIazure-cosmos~=4.9packages/graphrag-vectors/pyproject.toml
PyPIazure-identity~=1.25packages/graphrag-vectors/pyproject.toml
PyPIazure-search-documents~=12.0packages/graphrag-vectors/pyproject.toml
PyPIgraphrag-common==3.1.1packages/graphrag-vectors/pyproject.toml
PyPIlancedb~=0.34.0packages/graphrag-vectors/pyproject.toml
PyPInumpy~=2.1packages/graphrag-vectors/pyproject.toml
PyPIpyarrow~=25.0packages/graphrag-vectors/pyproject.toml
PyPIpydantic~=2.10packages/graphrag-vectors/pyproject.toml
PyPIazure-identity~=1.25packages/graphrag/pyproject.toml
PyPIazure-search-documents~=12.0packages/graphrag/pyproject.toml
PyPIazure-storage-blob~=12.24packages/graphrag/pyproject.toml
PyPIdevtools~=0.12packages/graphrag/pyproject.toml
PyPIgraphrag-cache==3.1.1packages/graphrag/pyproject.toml
PyPIgraphrag-chunking==3.1.1packages/graphrag/pyproject.toml
PyPIgraphrag-common==3.1.1packages/graphrag/pyproject.toml
PyPIgraphrag-input==3.1.1packages/graphrag/pyproject.toml
PyPIgraphrag-llm==3.1.1packages/graphrag/pyproject.toml
PyPIgraphrag-storage==3.1.1packages/graphrag/pyproject.toml
PyPIgraphrag-vectors==3.1.1packages/graphrag/pyproject.toml
PyPIgraspologic-native>=1.2,<1.3packages/graphrag/pyproject.toml
PyPIjson-repair~=0.30packages/graphrag/pyproject.toml
PyPInetworkx~=3.4packages/graphrag/pyproject.toml
PyPInltk~=3.9packages/graphrag/pyproject.toml
PyPInumpy~=2.1packages/graphrag/pyproject.toml
PyPIpandas~=3.0packages/graphrag/pyproject.toml
PyPIpyarrow~=25.0packages/graphrag/pyproject.toml
PyPIpydantic~=2.10packages/graphrag/pyproject.toml
PyPIspacy~=3.8packages/graphrag/pyproject.toml
PyPIblis~=1.0packages/graphrag/pyproject.toml
PyPItextblob~=0.18packages/graphrag/pyproject.toml
PyPItqdm~=4.67packages/graphrag/pyproject.toml
PyPItyping-extensions~=4.12packages/graphrag/pyproject.toml
PyPItyper~=0.16packages/graphrag/pyproject.toml
Todas las dependencias 427

Conjunto completo de dependencias resueltas según el grafo de dependencias de GitHub: 106 paquetes directos y 321 indirectos (transitivos). El cierre transitivo es completo cuando el repositorio incluye un lockfile.

RegistroPaqueteVersiónRelación
PyPIaiofilesdirecta
PyPIaiofiles24.1.0directa
PyPIaiofiles25.1.0directa
PyPIaltair5.5.0directa
PyPIazure-coredirecta
PyPIazure-core1.35.0directa
PyPIazure-core1.41.0directa
PyPIazure-cosmosdirecta
PyPIazure-cosmos4.16.1directa
PyPIazure-cosmos4.9.0directa
PyPIazure-identitydirecta
PyPIazure-identity1.23.1directa
PyPIazure-identity1.25.3directa
PyPIazure-search-documentsdirecta
PyPIazure-search-documents11.5.3directa
PyPIazure-search-documents12.0.0directa
PyPIazure-storage-blobdirecta
PyPIazure-storage-blob12.26.0directa
PyPIazure-storage-blob12.30.0directa
PyPIblisdirecta
PyPIblis1.2.1directa
PyPIblis1.3.3directa
PyPIdevtoolsdirecta
PyPIdevtools0.12.2directa
PyPIfastapidirecta
PyPIfastapi0.139.0directa
PyPIgraphrag2.5.0directa
PyPIgraphrag3.1.1directa
PyPIgraphrag-cache3.1.0directa
PyPIgraphrag-cache3.1.1directa
PyPIgraphrag-chunking3.1.0directa
PyPIgraphrag-chunking3.1.1directa
PyPIgraphrag-common3.1.0directa
PyPIgraphrag-common3.1.1directa
PyPIgraphrag-input3.1.0directa
PyPIgraphrag-input3.1.1directa
PyPIgraphrag-llm3.1.0directa
PyPIgraphrag-llm3.1.1directa
PyPIgraphrag-storage3.1.0directa
PyPIgraphrag-storage3.1.1directa
PyPIgraphrag-vectors3.1.0directa
PyPIgraphrag-vectors3.1.1directa
PyPIgraspologic-nativedirecta
PyPIgraspologic-native1.2.5directa
PyPIjinja2directa
PyPIjinja23.1.6directa
PyPIjson-repairdirecta
PyPIjson-repair0.30.3directa
PyPIjson-repair0.61.4directa
PyPIlancedbdirecta
PyPIlancedb0.17.0directa
PyPIlancedb0.34.0directa
PyPIlitellm1.86.2directa
PyPIlitellm1.92.0directa
PyPImarkitdowndirecta
PyPImarkitdown0.1.6directa
PyPInest-asyncio2directa
PyPInest-asyncio21.7.2directa
PyPInetworkxdirecta
PyPInetworkx3.4.2directa
PyPInetworkx3.5directa
PyPInetworkx3.6.1directa
PyPInltkdirecta
PyPInltk3.10.0directa
PyPInltk3.9.1directa
PyPInumpydirecta
PyPInumpy1.26.4directa
PyPInumpy2.4.6directa
PyPInumpy2.5.1directa
PyPIorjsondirecta
PyPIorjson3.11.9directa
PyPIpandasdirecta
PyPIpandas2.3.1directa
PyPIpandas3.0.3directa
PyPIpyarrowdirecta
PyPIpyarrow21.0.0directa
PyPIpyarrow25.0.0directa
PyPIpydanticdirecta
PyPIpydantic2.11.7directa
PyPIpydantic2.13.4directa
PyPIpython-dotenvdirecta
PyPIpython-dotenv1.1.1directa
PyPIpython-dotenv1.2.2directa
PyPIpyyamldirecta
PyPIpyyaml6.0.2directa
PyPIpyyaml6.0.3directa
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Avisos de dependencias 0

Instalar pypi:graphrag@3.1.1 arrastra 113 paquetes, directos y transitivos: 0 tienen avisos conocidos, de los cuales 0 son dependencias directas.

Ningún aviso conocido afecta a las dependencias evaluadas.

Un aviso significa que la versión registrada en el grafo de dependencias cae dentro del rango afectado de un aviso. No se analiza la alcanzabilidad, y el grafo incluye fijaciones de desarrollo y prueba: un hallazgo puede referirse al utillaje y no al software distribuido.

Informe JSON sin procesar legible por máquina
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          "headline": "Pin litellm dependency (#2290)",
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          "headline": "reconfigure vector store size (#2281)",
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          "headline": "Release v3.0.6 (#2267)",
          "author_name": "Dayenne Souza",
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          "committed_at": "2026-03-06T20:02:49Z",
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          "is_bot": false,
          "headline": "nlp streaming (#2264)",
          "author_name": "Dayenne Souza",
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          "headline": "remove relationships with phantom entities (#2261)",
          "author_name": "Dayenne Souza",
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          "is_bot": false,
          "headline": "vector load_documents in batches (#2251)",
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          "headline": "fix csv file reader (#2248)",
          "author_name": "Dayenne Souza",
          "author_login": "dayesouza",
          "committed_at": "2026-02-25T01:10:59Z",
          "body_truncated": false,
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        {
          "oid": "a82d186fd2ca128ebbfa04f7b3675a338f855320",
          "body": "* Release v3.0.4\n\n* release v3.0.4",
          "is_bot": false,
          "headline": "Release v3.0.4 (#2247)",
          "author_name": "gaudyb",
          "author_login": "gaudyb",
          "committed_at": "2026-02-24T22:51:02Z",
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          "body": "Co-authored-by: Gaudy Blanco <gaudy-microsoft@MacBook-Pro-m4-Gaudy-For-Work.local>",
          "is_bot": false,
          "headline": "Release v3.0.3 (#2245)",
          "author_name": "gaudyb",
          "author_login": "gaudyb",
          "committed_at": "2026-02-24T20:54:28Z",
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          "body": "add stats write",
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          "headline": "write stats per workflow (#2244)",
          "author_name": "Dayenne Souza",
          "author_login": "dayesouza",
          "committed_at": "2026-02-23T22:17:21Z",
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          "body": "* streaming create_final_documents\n\n* add semversioner",
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          "headline": "streaming create_final_documents (#2243)",
          "author_name": "Dayenne Souza",
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          "headline": "streaming finalize_graph  (#2240)",
          "author_name": "Dayenne Souza",
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        },
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          "body": "…s (#2236)\n\n* feat(graphrag-vectors): add filtering, timestamps, and CRUD operations\n\nImplement the vector store enhancements from the graphrag-vectors-design spec:\n\nNew modules:\n- filtering.py: Pydantic-based filter expression system with F builder,\n  operator overloads, JSON serialization, client-\n[…]\nuet, embeddings.text_unit_text.parquet)\n- Add CPY001, SLF001, DTZ005 to notebook lint ignores in pyproject.toml\n\n* refactor: extract model/tokenizer creation from generate_text_embeddings into callers",
          "is_bot": false,
          "headline": "feat(graphrag-vectors): add filtering, timestamps, and CRUD operation…",
          "author_name": "Nathan Evans",
          "author_login": "natoverse",
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          "body": "* addd streaming\n\n* fixes",
          "is_bot": false,
          "headline": "generate_text_embeddings streaming (#2241)",
          "author_name": "Dayenne Souza",
          "author_login": "dayesouza",
          "committed_at": "2026-02-20T22:53:32Z",
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          "oid": "bf1034a7eba75d15a1e1ea48d152dcc90a22387d",
          "body": "* addd streaming to create_final_text_units - also removed pandas from its internal workflow logic\n\n* fix comment\n\n* fix test\n\n* fix typo\n\n* add suggestion\n\n* add csv tests data\n\n* fix spell",
          "is_bot": false,
          "headline": "Streaming create_final_text_units (#2238)",
          "author_name": "Dayenne Souza",
          "author_login": "dayesouza",
          "committed_at": "2026-02-20T14:18:00Z",
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          "is_coding_agent": false
        },
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          "oid": "ac7ce32b61390402fd83e381cf40837a61ad4fe1",
          "body": "* add manual release instructions\n\n* create streaming\n\n* fix deleted file\n\n* addd file\n\n* fix check\n\n* add consistency\n\n* fix logic",
          "is_bot": false,
          "headline": "Streaming create communities (#2237)",
          "author_name": "Dayenne Souza",
          "author_login": "dayesouza",
          "committed_at": "2026-02-19T18:39:58Z",
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        {
          "oid": "6d9f0dcf3004a83ef55398eada11fecd75f7307a",
          "body": "* add release doc\n\n* fix spellcheck",
          "is_bot": false,
          "headline": "add release doc (#2235)",
          "author_name": "Dayenne Souza",
          "author_login": "dayesouza",
          "committed_at": "2026-02-19T00:14:38Z",
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        {
          "oid": "20d30fd93b4f3260e8f9522925063bcff4791133",
          "body": "* work in progress\n\n* cosmosdb output error fix\n\n* semserver update\n\n* remove unnecessary code\n\n* clean code\n\n* remove unnecessary prints",
          "is_bot": false,
          "headline": "Cosmosdb communities bug (#2232)",
          "author_name": "gaudyb",
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          "oid": "79d7a70c945f7f6b2623072895145c8da0dd83ae",
          "body": "* add smoke tests for output csv\n\n* change text fixture test\n\n* change test\n\n* add semver\n\n* run format\n\n---------\n\nCo-authored-by: Nathan Evans <github@talkswithnumbers.com>",
          "is_bot": false,
          "headline": "modify smoke tests to include csv table provider (#2229)",
          "author_name": "Dayenne Souza",
          "author_login": "dayesouza",
          "committed_at": "2026-02-13T22:23:26Z",
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        },
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          "body": "* add streaming read\n\n* fix formatting\n\n* create csv streaming write\n\n* add parquettable to simulate streaming\n\n* add sample rows return\n\n* add load_input_documents and truncate mode to Table\n\n* add semver\n\n* addd csv output reader fix\n\n* run formatter\n\n* add csv config",
          "is_bot": false,
          "headline": "load_input_documents and create_base_text_units streaming (#2221)",
          "author_name": "Dayenne Souza",
          "author_login": "dayesouza",
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            "name": "Security posture",
            "note": "Excluded from scoring (no data or not applicable): Packaging, Signed-Releases. Remaining weights renormalized.",
            "notes": [
              {
                "code": "excluded_no_data",
                "params": {
                  "components": [
                    "packaging",
                    "signed_releases"
                  ]
                }
              },
              {
                "code": "weights_renormalized",
                "params": {}
              }
            ],
            "value": 66,
            "inputs": {
              "source": "openssf_scorecard",
              "checks_evaluated": 16,
              "scorecard_version": "v5.5.0",
              "checks_inconclusive": 2,
              "scorecard_aggregate": 6.6
            },
            "components": [
              {
                "key": "binary_artifacts",
                "name": "Binary-Artifacts",
                "detail": "no binaries found in the repo",
                "points": 7.5,
                "status": "met",
                "details": [],
                "max_points": 7.5
              },
              {
                "key": "branch_protection",
                "name": "Branch-Protection",
                "detail": "branch protection is not maximal on development and all release branches",
                "points": 3.8,
                "status": "partial",
                "details": [],
                "max_points": 7.5
              },
              {
                "key": "ci_tests",
                "name": "CI-Tests",
                "detail": "30 out of 30 merged PRs checked by a CI test -- score normalized to 10",
                "points": 2.5,
                "status": "met",
                "details": [],
                "max_points": 2.5
              },
              {
                "key": "cii_best_practices",
                "name": "CII-Best-Practices",
                "detail": "no effort to earn an OpenSSF best practices badge detected",
                "points": 0,
                "status": "missed",
                "details": [],
                "max_points": 2.5
              },
              {
                "key": "code_review",
                "name": "Code-Review",
                "detail": "all changesets reviewed",
                "points": 7.5,
                "status": "met",
                "details": [],
                "max_points": 7.5
              },
              {
                "key": "contributors",
                "name": "Contributors",
                "detail": "project has 9 contributing companies or organizations",
                "points": 2.5,
                "status": "met",
                "details": [],
                "max_points": 2.5
              },
              {
                "key": "dangerous_workflow",
                "name": "Dangerous-Workflow",
                "detail": "no dangerous workflow patterns detected",
                "points": 10,
                "status": "met",
                "details": [],
                "max_points": 10
              },
              {
                "key": "dependency_update_tool",
                "name": "Dependency-Update-Tool",
                "detail": "update tool detected",
                "points": 7.5,
                "status": "met",
                "details": [],
                "max_points": 7.5
              },
              {
                "key": "fuzzing",
                "name": "Fuzzing",
                "detail": "project is not fuzzed",
                "points": 0,
                "status": "missed",
                "details": [],
                "max_points": 5
              },
              {
                "key": "license",
                "name": "License",
                "detail": "license file detected",
                "points": 2.5,
                "status": "met",
                "details": [],
                "max_points": 2.5
              },
              {
                "key": "maintained",
                "name": "Maintained",
                "detail": "14 commit(s) and 8 issue activity found in the last 90 days -- score normalized to 10",
                "points": 7.5,
                "status": "met",
                "details": [],
                "max_points": 7.5
              },
              {
                "key": "packaging",
                "name": "Packaging",
                "detail": "packaging workflow not detected",
                "points": 0,
                "status": "excluded",
                "details": [
                  {
                    "code": "no_data",
                    "params": {}
                  }
                ],
                "max_points": 5
              },
              {
                "key": "pinned_dependencies",
                "name": "Pinned-Dependencies",
                "detail": "dependency not pinned by hash detected -- score normalized to 0",
                "points": 0,
                "status": "missed",
                "details": [],
                "max_points": 5
              },
              {
                "key": "sast",
                "name": "SAST",
                "detail": "SAST tool is run on all commits",
                "points": 5,
                "status": "met",
                "details": [],
                "max_points": 5
              },
              {
                "key": "security_policy",
                "name": "Security-Policy",
                "detail": "security policy file detected",
                "points": 5,
                "status": "met",
                "details": [],
                "max_points": 5
              },
              {
                "key": "signed_releases",
                "name": "Signed-Releases",
                "detail": "no releases found",
                "points": 0,
                "status": "excluded",
                "details": [
                  {
                    "code": "no_data",
                    "params": {}
                  }
                ],
                "max_points": 7.5
              },
              {
                "key": "token_permissions",
                "name": "Token-Permissions",
                "detail": "detected GitHub workflow tokens with excessive permissions",
                "points": 0,
                "status": "missed",
                "details": [],
                "max_points": 7.5
              },
              {
                "key": "vulnerabilities",
                "name": "Vulnerabilities",
                "detail": "85 existing vulnerabilities detected",
                "points": 0,
                "status": "missed",
                "details": [],
                "max_points": 7.5
              }
            ]
          },
          {
            "key": "dependency_advisories",
            "band": "excellent",
            "name": "Dependency advisories",
            "note": "Excluded from scoring (no data or not applicable): No advisories left outstanding. Remaining weights renormalized. Matched the pypi:graphrag@3.1.1 runtime dependency closure — what installing the published package pulls in — 113 packages. Reachability is not analyzed.",
            "notes": [
              {
                "code": "excluded_no_data",
                "params": {
                  "components": [
                    "no_advisories_left_outstanding"
                  ]
                }
              },
              {
                "code": "weights_renormalized",
                "params": {}
              },
              {
                "code": "advisories_scope_published",
                "params": {
                  "package": "pypi:graphrag@3.1.1",
                  "assessed": 113
                }
              },
              {
                "code": "advisories_reachability",
                "params": {}
              }
            ],
            "value": 100,
            "inputs": {
              "source": "osv",
              "advisories": 0,
              "affected_packages": 0,
              "assessed_packages": 113,
              "unassessed_packages": 0,
              "affected_by_severity": "none",
              "direct_affected_packages": 0
            },
            "components": [
              {
                "key": "direct_dependencies_free_of_known_advisories",
                "name": "Direct dependencies free of known advisories",
                "detail": "no direct dependency carries a known advisory",
                "points": 35,
                "status": "met",
                "details": [
                  {
                    "code": "no_direct_advisories",
                    "params": {}
                  }
                ],
                "max_points": 35
              },
              {
                "key": "indirect_dependencies_free_of_known_advisories",
                "name": "Indirect dependencies free of known advisories",
                "detail": "no indirect dependency carries a known advisory",
                "points": 25,
                "status": "met",
                "details": [
                  {
                    "code": "no_indirect_advisories",
                    "params": {}
                  }
                ],
                "max_points": 25
              },
              {
                "key": "no_advisories_left_outstanding",
                "name": "No advisories left outstanding",
                "detail": "no advisory carries a publication date",
                "points": 0,
                "status": "excluded",
                "details": [
                  {
                    "code": "advisories_no_publication_date",
                    "params": {}
                  }
                ],
                "max_points": 40
              }
            ]
          },
          {
            "key": "malicious_dependencies",
            "band": "excellent",
            "name": "Malicious dependencies",
            "note": null,
            "notes": [],
            "value": 100,
            "inputs": {
              "source": "osv",
              "meaning": "reported as a malicious package by the OpenSSF corpus; the remedy is removal or moving off the compromised name, never an upgrade of the same artifact. Versions the registry has since pulled are listed but not scored",
              "packages": [],
              "red_flag": false,
              "assessed_packages": 113,
              "malicious_packages": 0,
              "direct_malicious_packages": 0,
              "withdrawn_malicious_packages": 0,
              "installable_malicious_packages": 0
            },
            "components": [
              {
                "key": "no_dependency_reported_as_a_malicious_package",
                "name": "No dependency reported as a malicious package",
                "detail": "no dependency is reported as a malicious package",
                "points": 100,
                "status": "met",
                "details": [
                  {
                    "code": "no_malicious_dependencies",
                    "params": {}
                  }
                ],
                "max_points": 100
              }
            ]
          },
          {
            "key": "high_risk_jurisdiction_exposure",
            "band": "excellent",
            "name": "High-Risk Jurisdiction Exposure",
            "note": "Only high-confidence self-published location evidence affects this multiplier. Ambiguous matches are review-only; country evidence is not proof of nationality, citizenship, legal registration, malicious intent, or sanctions status.",
            "notes": [
              {
                "code": "jurisdiction_evidence_limits",
                "params": {}
              }
            ],
            "value": 100,
            "inputs": {
              "meaning": "self-published location evidence; not nationality or citizenship",
              "red_flag": false,
              "exposures": [],
              "policy_countries": [
                "Russia",
                "Iran",
                "North Korea"
              ],
              "review_only_matches": 0,
              "assessed_self_published_locations": 15
            },
            "components": [
              {
                "key": "policy_exposure_multiplier",
                "name": "Policy exposure multiplier",
                "detail": "no confirmed policy-scope location match",
                "points": 100,
                "status": "met",
                "details": [
                  {
                    "code": "jurisdiction_no_match",
                    "params": {}
                  }
                ],
                "max_points": 100
              }
            ]
          }
        ],
        "description": "Are visible security and supply-chain practices strong, with no malicious dependency and no unresolved high-risk jurisdiction exposure?"
      },
      {
        "key": "ai_readiness",
        "band": "moderate",
        "name": "AI Readiness",
        "value": 54,
        "weight": 0,
        "metrics": [
          {
            "key": "ai_agent_context",
            "band": "at_risk",
            "name": "Agent context & guidance",
            "note": null,
            "notes": [],
            "value": 40,
            "inputs": {
              "has_llms_txt": false,
              "legible_history_share": 0.99,
              "agent_instruction_files": [],
              "agent_instruction_max_bytes": null
            },
            "components": [
              {
                "key": "agent_instructions",
                "name": "Agent instructions",
                "detail": "no CLAUDE.md / AGENTS.md / editor rules",
                "points": 0,
                "status": "missed",
                "details": [
                  {
                    "code": "no_agent_instructions",
                    "params": {}
                  }
                ],
                "max_points": 45
              },
              {
                "key": "machine_readable_docs_llms_txt",
                "name": "Machine-readable docs (llms.txt)",
                "detail": null,
                "points": 0,
                "status": "missed",
                "details": [],
                "max_points": 15
              },
              {
                "key": "legible_commit_history",
                "name": "Legible commit history",
                "detail": "99 of 100 human commits state their intent (structured subject or explanatory body)",
                "points": 40,
                "status": "met",
                "details": [
                  {
                    "code": "legible_history",
                    "params": {
                      "legible": 99,
                      "sampled": 100
                    }
                  }
                ],
                "max_points": 40
              }
            ]
          },
          {
            "key": "ai_verify_loop",
            "band": "moderate",
            "name": "Verify loop (build / test / typecheck)",
            "note": null,
            "notes": [],
            "value": 58,
            "inputs": {
              "has_nix": false,
              "has_tests": true,
              "lockfiles": [
                "uv.lock"
              ],
              "has_dockerfile": true,
              "typed_language": false,
              "bootstrap_files": [],
              "has_devcontainer": false,
              "has_linter_config": false,
              "typecheck_configs": [
                "packages/graphrag-cache/graphrag_cache/py.typed",
                "packages/graphrag-common/graphrag_common/py.typed",
                "packages/graphrag-llm/graphrag_llm/py.typed",
                "packages/graphrag-storage/graphrag_storage/py.typed",
                "packages/graphrag/graphrag/py.typed"
              ],
              "agent_commit_share": 0.07,
              "toolchain_manifests": [],
              "dependency_bot_commit_share": 0
            },
            "components": [
              {
                "key": "one_command_bootstrap",
                "name": "One-command bootstrap",
                "detail": null,
                "points": 0,
                "status": "missed",
                "details": [],
                "max_points": 18
              },
              {
                "key": "automated_tests",
                "name": "Automated tests",
                "detail": null,
                "points": 22,
                "status": "met",
                "details": [],
                "max_points": 22
              },
              {
                "key": "lint_format_config",
                "name": "Lint / format config",
                "detail": null,
                "points": 0,
                "status": "missed",
                "details": [],
                "max_points": 11
              },
              {
                "key": "static_type_checking",
                "name": "Static type checking",
                "detail": "packages/graphrag-cache/graphrag_cache/py.typed, packages/graphrag-common/graphrag_common/py.typed, packages/graphrag-llm/graphrag_llm/py.typed, packages/graphrag-storage/graphrag_storage/py.typed, packages/graphrag/graphrag/py.typed",
                "points": 11,
                "status": "met",
                "details": [
                  {
                    "code": "file_list",
                    "params": {
                      "files": "packages/graphrag-cache/graphrag_cache/py.typed, packages/graphrag-common/graphrag_common/py.typed, packages/graphrag-llm/graphrag_llm/py.typed, packages/graphrag-storage/graphrag_storage/py.typed, packages/graphrag/graphrag/py.typed"
                    }
                  }
                ],
                "max_points": 11
              },
              {
                "key": "reproducible_environment",
                "name": "Reproducible environment",
                "detail": "Dockerfile, lockfile",
                "points": 10,
                "status": "met",
                "details": [
                  {
                    "code": "file_list",
                    "params": {
                      "files": "Dockerfile, lockfile"
                    }
                  }
                ],
                "max_points": 10
              },
              {
                "key": "demonstrated_agent_practice",
                "name": "Demonstrated agent practice",
                "detail": "7 of the last 100 commits agent-authored or agent-credited",
                "points": 10,
                "status": "met",
                "details": [
                  {
                    "code": "agent_authored_commits",
                    "params": {
                      "count": 7,
                      "sampled": 100
                    }
                  }
                ],
                "max_points": 10
              },
              {
                "key": "automated_maintenance",
                "name": "Automated maintenance",
                "detail": "dependency automation configured, none observed in the sampled commits",
                "points": 5,
                "status": "partial",
                "details": [
                  {
                    "code": "dependency_bot_config_only",
                    "params": {}
                  }
                ],
                "max_points": 8
              },
              {
                "key": "openssf_scorecard_pinned_dependencies",
                "name": "OpenSSF Scorecard: Pinned-Dependencies",
                "detail": "dependency not pinned by hash detected -- score normalized to 0",
                "points": 0,
                "status": "missed",
                "details": [],
                "max_points": 10
              }
            ]
          },
          {
            "key": "ai_code_legibility",
            "band": "good",
            "name": "Code legibility for models",
            "note": null,
            "notes": [],
            "value": 82,
            "inputs": {
              "primary_language": "Python",
              "largest_source_bytes": 22070,
              "source_files_sampled": 573,
              "oversized_source_files": 0
            },
            "components": [
              {
                "key": "type_checkable_code",
                "name": "Type-checkable code",
                "detail": "Python with type-check config (packages/graphrag-cache/graphrag_cache/py.typed, packages/graphrag-common/graphrag_common/py.typed, packages/graphrag-llm/graphrag_llm/py.typed, packages/graphrag-storage/graphrag_storage/py.typed, packages/graphrag/graphrag/py.typed)",
                "points": 27,
                "status": "partial",
                "details": [
                  {
                    "code": "typecheck_config_language",
                    "params": {
                      "files": "packages/graphrag-cache/graphrag_cache/py.typed, packages/graphrag-common/graphrag_common/py.typed, packages/graphrag-llm/graphrag_llm/py.typed, packages/graphrag-storage/graphrag_storage/py.typed, packages/graphrag/graphrag/py.typed",
                      "language": "Python"
                    }
                  }
                ],
                "max_points": 45
              },
              {
                "key": "manageable_file_sizes",
                "name": "Manageable file sizes",
                "detail": "0/573 source files over 60KB",
                "points": 55,
                "status": "met",
                "details": [
                  {
                    "code": "oversized_source_files",
                    "params": {
                      "kb": 60,
                      "sampled": 573,
                      "oversized": 0
                    }
                  }
                ],
                "max_points": 55
              }
            ]
          },
          {
            "key": "ai_interfaces",
            "band": "at_risk",
            "name": "Machine-readable interfaces",
            "note": null,
            "notes": [],
            "value": 40,
            "inputs": {
              "example_dirs": [
                "notebooks"
              ],
              "has_mcp_signal": false,
              "api_schema_files": []
            },
            "components": [
              {
                "key": "api_schema_openapi_graphql_proto",
                "name": "API schema (OpenAPI/GraphQL/proto)",
                "detail": null,
                "points": 0,
                "status": "missed",
                "details": [],
                "max_points": 40
              },
              {
                "key": "mcp_server",
                "name": "MCP server",
                "detail": null,
                "points": 0,
                "status": "missed",
                "details": [],
                "max_points": 20
              },
              {
                "key": "runnable_examples",
                "name": "Runnable examples",
                "detail": "notebooks",
                "points": 40,
                "status": "met",
                "details": [
                  {
                    "code": "file_list",
                    "params": {
                      "files": "notebooks"
                    }
                  }
                ],
                "max_points": 40
              }
            ]
          }
        ],
        "description": "How well is the repo equipped to be developed and maintained with AI coding agents? An independent, experimental badge — weight 0.0, so it is surfaced on its own and does not affect the overall health score."
      }
    ],
    "metrics_version": "1.13.0"
  },
  "warnings": [
    "Star history unavailable: GitHub GraphQL error: Resource not accessible by personal access token",
    "Could not fetch pypi package 'graphrag-monorepo' from its registry",
    "Could not fetch pypi package 'unified-copilot' from its registry"
  ],
  "report_type": "repository",
  "generated_at": "2026-07-26T21:40:55.520352Z",
  "schema_version": "0.27.0",
  "badge_url": "https://raw.githubusercontent.com/inspect-software/badges/main/v1/m/microsoft/graphrag.svg",
  "full_name": "microsoft/graphrag",
  "license_state": "standard",
  "license_spdx": "MIT"
}

Las puntuaciones son señales, no garantías. Reflejan prácticas públicamente visibles en GitHub; no son una auditoría de código ni una garantía de seguridad.

Los datos ausentes se excluyen y los pesos se renormalizan; nunca se puntúan como cero. La metodología es versionada y abierta: métricas v1.13.0, esquema v0.27.0 — metodología completa · wiki de métricas.

Cómo se sitúa un resultado dentro del registro general: estadísticas agregadasPyPI.